Fermionic quantum field theories as probabilistic cellular automata

A class of fermionic quantum field theories with interactions is shown to be equivalent to probabilistic cellular automata, namely cellular automata with a probability distribution for the initial states. Probabilistic cellular automata on a one-dimensional lattice are equivalent to two-dimensional...

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Bibliographic Details
Main Author: Wetterich, Christof (Author)
Format: Article (Journal)
Language:English
Published: 8 April 2022
In: Physical review
Year: 2022, Volume: 105, Issue: 7, Pages: 1-52
ISSN:2470-0029
DOI:10.1103/PhysRevD.105.074502
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1103/PhysRevD.105.074502
Verlag, lizenzpflichtig, Volltext: https://link.aps.org/doi/10.1103/PhysRevD.105.074502
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Author Notes:C. Wetterich
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Summary:A class of fermionic quantum field theories with interactions is shown to be equivalent to probabilistic cellular automata, namely cellular automata with a probability distribution for the initial states. Probabilistic cellular automata on a one-dimensional lattice are equivalent to two-dimensional quantum field theories for fermions. They can be viewed as generalized Ising models on a square lattice and therefore as classical statistical systems. As quantum field theories they are quantum systems. Thus quantum mechanics emerges from classical statistics. As an explicit example for an interacting fermionic quantum field theory we describe a type of discretized Thirring model as a cellular automaton. The updating rule of the automaton is encoded in the step evolution operator that can be expressed in terms of fermionic annihilation and creation operators. The complex structure of quantum mechanics is associated to particle-hole transformations. The naive continuum limit exhibits Lorentz symmetry. We exploit the equivalence to quantum field theory in order to show how quantum concepts as wave functions, density matrix, noncommuting operators for observables and similarity transformations are convenient and useful concepts for the description of probabilistic cellular automata.
Item Description:Gesehen am 16.05.2022
Physical Description:Online Resource
ISSN:2470-0029
DOI:10.1103/PhysRevD.105.074502